Case -
Increasing probabilities in getting funded using Natural Language Processing


The challenge

Our customer makes funding applications with other external companies and partners so that they can then send them to the grant funding parties. It takes a reasonable effort to prepare a funding application and there are plenty of such applications to be completed each year. Despite that, our customer is obliged to make many funding applications and only a small amount of them get approved. To improve the chances on getting funded, there was a clear opportunity to understand the different study fields getting approved for funding and optimize application with the gained information.


Our solution

Our customer wanted to learn which research areas and studies within their institution had had an advantage over other institutions to formulate succeeding applications. This meant going through all the abstracts of bachelors and masters publications. We gained insight with our Varis toolkit and also web scraper with analyzing over 3000 theses.



With the help of the provided visual maps, our customer can now provide to the quantitative evidence about their strengths and preparing for new funding applications with a higher and more solid chance of success  

Keywords, technologies and tools

  • Natural Language Processing 

  • Web scraping

  • Graphviz

  • Varis

  • Python


For more information


Pekka Lehti


+358 45 123 6610


Marko Laakso Print (1).jpg

Marko Laakso


+358 45 135 4248